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Dead-Seq:从死亡细胞基因组学中发现合成致死相互作用。

Dead-Seq: Discovering Synthetic Lethal Interactions from Dead Cells Genomics.

作者信息

Blanco-Fernandez Joan, Jourdain Alexis A

机构信息

Department of Immunobiology, University of Lausanne, Epalinges, Switzerland.

出版信息

Methods Mol Biol. 2023;2661:329-342. doi: 10.1007/978-1-0716-3171-3_19.

Abstract

Pooled genetic screens have revolutionized the field of functional genomics, yet perturbations that decrease fitness, such as those leading to synthetic lethality, have remained difficult to quantify at the genomic level. We and colleagues previously developed "death screening," a protocol based on the purification of dead cells in genetic screens, and used it to identify a set of genes necessary for mitochondrial gene expression, translation, and oxidative phosphorylation (OXPHOS), thus offering new possibilities for the diagnosis of mitochondrial disorders. Here, we describe Dead-Seq, a refined protocol for death screening that is compatible with most pooled screening protocols, including genome-wide CRISPR/Cas9 screening. Dead-Seq converts negative-selection screens into positive-selection screens and generates high-quality data directly from dead cells, at limited sequencing costs.

摘要

汇集式基因筛选彻底改变了功能基因组学领域,然而,降低适应性的干扰因素,如导致合成致死的因素,在基因组水平上仍难以量化。我和同事们此前开发了“死亡筛选”,这是一种基于在基因筛选中纯化死细胞的方案,并利用它来鉴定一组线粒体基因表达、翻译和氧化磷酸化(OXPHOS)所必需的基因,从而为线粒体疾病的诊断提供了新的可能性。在这里,我们描述了Dead-Seq,这是一种改进的死亡筛选方案,它与大多数汇集式筛选方案兼容,包括全基因组CRISPR/Cas9筛选。Dead-Seq将负选择筛选转化为正选择筛选,并以有限的测序成本直接从死细胞中生成高质量数据。

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